Call for papers Special session on Machine Learning and AI in Digital Healthcare and Personalised Medicine. Part of Evo* 2021 – Seville, Spain EvoMED is a multidisciplinary workshop that brings together researchers working in the fields of personalised medicine, medical devices; clinical diagnostics, and patient monitoring that apply advanced evolutionary computation techniques to address critical problems in digital healthcare and medical applications. As the demand on health systems and hospitals worldwide becomes unsustainable, there has been an increasing interest in applying novel approaches, such as evolutionary computation, to the next generation of healthcare solutions. As the mode of treatment turns from the hospital to the home, there has been a particular focus on personalized medicine in the hope of improving patient care and reduce costs. Topics of interest include, but are not limited to, any of the following:
* Medical imaging * Medical signal processing * Medical text analysis * Clinical diagnosis and therapy * Data mining medical data and records * Clinical expert systems * Modelling and simulation of medical processes * Drug description analysis * Genomic-based clinical studies * Patient-centric care * Patient/hospital management optimisation Chairs Stephen Smith, (stephen.sm...@york.ac.uk<mailto:stephen.sm...@york.ac.uk> ), University of York, York, UK Marta Vallejo, (m.vall...@hw.ac.uk<mailto:m.vall...@hw.ac.uk>), Heriot-Watt University, Edinburgh, UK Publication and submission details All the papers submitted to this special session will be part and will follow the same procedure than the regular papers submitted to EvoApplications<http://www.google.com/url?q=http%3A%2F%2Fwww.evostar.org%2F2020%2F%3Fpage_id%3D80&sa=D&sntz=1&usg=AFQjCNG0g1n65kpEajG-pGo97ZWqogofIg>. Important Dates Submission deadline: 1 November 2020 Notification deadline: TBA Camera ready deadline: TBA EvoStar Conference: 7-9 April 2021 ----------------------------------------------------------------- Dr. Marta Vallejo Tenure Track Research Fellow in Biomedical Signal and Image Processing Phone +44 (0)131 451 3081 Earl Mountbatten Building, Room EMG.04 School of Engineering & Physical Sciences; Sensors, Signals & Systems Heriot-Watt University Edinburgh, EH14 4AS, UK [cid:part4.E9F67F73.56D0A7EF@hw.ac.uk] [https://ipmcdn.avast.com/images/icons/icon-envelope-tick-green-avg-v1.png]<http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=emailclient> Virus-free. www.avg.com<http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=emailclient> ________________________________ Founded in 1821, Heriot-Watt is a leader in ideas and solutions. With campuses and students across the entire globe we span the world, delivering innovation and educational excellence in business, engineering, design and the physical, social and life sciences. This email is generated from the Heriot-Watt University Group, which includes: 1. Heriot-Watt University, a Scottish charity registered under number SC000278 2. Heriot- Watt Services Limited (Oriam), Scotland's national performance centre for sport. Heriot-Watt Services Limited is a private limited company registered is Scotland with registered number SC271030 and registered office at Research & Enterprise Services Heriot-Watt University, Riccarton, Edinburgh, EH14 4AS. The contents (including any attachments) are confidential. If you are not the intended recipient of this e-mail, any disclosure, copying, distribution or use of its contents is strictly prohibited, and you should please notify the sender immediately and then delete it (including any attachments) from your system.
_______________________________________________ uai mailing list uai@engr.orst.edu https://it.engineering.oregonstate.edu/mailman/listinfo/uai
